Implementation of GLCM/GLDV-based Texture Algorithm and Its Application to High Resolution Imagery Analysis

GLCM/GLDV 기반 Texture 알고리즘 구현과 고 해상도 영상분석 적용

  • Lee Kiwon (Dept. of Information System Engineering, Hansung University) ;
  • Jeon So-Hee (Dept. of Geoscience Education, Seoul National University) ;
  • Kwon Byung-Doo (Dept. of Geoscience Education, Seoul National University)
  • 이기원 (한성대학교 정보시스템공학과) ;
  • 전소희 (서울대학교 지구과학교육과) ;
  • 권병두 (서울대학교 지구과학교육과)
  • Published : 2005.04.01

Abstract

Texture imaging, which means texture image creation by co-occurrence relation, has been known as one of the useful image analysis methodologies. For this purpose, most commercial remote sensing software provides texture analysis function named GLCM (Grey Level Co-occurrence Matrix). In this study, texture-imaging program based on GLCM algorithm is newly implemented. As well, texture imaging modules for GLDV (Grey Level Difference Vector) are contained in this program. As for GLCM/GLDV Texture imaging parameters, it composed of six types of second order texture functions such as Homogeneity, Dissimilarity, Energy, Entropy, Angular Second Moment, and Contrast. As for co-occurrence directionality in GLCM/GLDV, two direction modes such as Omni-mode and Circular mode newly implemented in this program are provided with basic eight-direction mode. Omni-mode is to compute all direction to avoid directionality complexity in the practical level, and circular direction is to compute texture parameters by circular direction surrounding a target pixel in a kernel. At the second phase of this study, some case studies with artificial image and actual satellite imagery are carried out to analyze texture images in different parameters and modes by correlation matrix analysis. It is concluded that selection of texture parameters and modes is the critical issues in an application based on texture image fusion.

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